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- W2023347927 abstract "The property of identifiability is an important consideration on estimating the parameters in a mixture of distributions. Also classification of a random variable based on a mixture can be meaning fully discussed only if the class of all finite mixtures is identifiable. The problem of identifiability of finite mixture of Gompertz distributions is studied. A procedure is presented for finding maximum likelihood estimates of the parameters of a mixture of two Gompertz distributions, using classified and unclassified observations. Based on small sample size, estimation of a nonlinear discriminant function is considered. Throughout simulation experiments, the performance of the corresponding estimated nonlinear discriminant function is investigated." @default.
- W2023347927 created "2016-06-24" @default.
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- W2023347927 date "2003-12-01" @default.
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- W2023347927 title "On MLE of a nonlinear discriminant function from a mixture of two Gompertz distributions based on small sample size" @default.
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- W2023347927 doi "https://doi.org/10.1080/0094965031000097296" @default.
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